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Normalized Hermitian inequality SDPs have equal primal and dual values

Statement

Let n≥0 and m≥1 be finite integers. Consider the Hermitian inequality-form primal and dual of Finite semidefinite primal-dual pair, with ∥Aj∥,∥C∥≤1, A1=I, and b1=R>0. Suppose the primal feasible set is nonempty. Then that set is compact, the primal supremum is attained, and the primal and dual values satisfy p∗=d∗∈[−R,R]. The dual has a feasible point whose coordinates are all strictly positive and whose matrix slack is positive definite. No strict primal feasibility is required. Dual optimal attainment remains a separate promise: if a dual optimum y∗ with ∥y∗∥1≤r, r≥1, is supplied, then b⋅y∗=p∗ with the same norm bound.

Facts & Assumptions

Given: The finite Hermitian primal-dual pair, normalization, and primal nonemptiness in the Statement.

[F1]

Finite semidefinite primal-dual pair and Trace of a product of Hermitian matrices is real: the primal maximizes tr⁡(CX) subject to X⪰0 and tr⁡(AjX)≤bj; the dual minimizes b⋅y subject to y≥0 and ∑jyjAj−C⪰0. All these trace quantities are real.

[F2]

Non-negative and positive operators and A non-negative operator is equivalently self-adjoint with nonnegative eigenvalues, a positive semidefinite matrix in an orthonormal basis, or an operator of the form S^*S: a finite complex Hermitian positive semidefinite matrix has an orthonormal eigenbasis with nonnegative eigenvalues; positive definite means a strictly positive quadratic form on every nonzero vector.

[F3]

The trace tr⁡(A) as the sum of the diagonal entries: trace is the diagonal sum, including the empty sum for n=0.

[F7]

A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value: a continuous real function on a nonempty compact metric space attains its extrema, without choice.

[F8]

Interior, closure, boundary, limit point, isolated point and dense subset of a metric space: a point lies in a set's closure exactly when every neighborhood meets the set.

[F9]

A point outside a nonempty closed convex set is strictly separated from it: a point outside a nonempty closed convex subset of Rk, k≥1, has a strict separating real linear functional.

Proof

1.1givenF1F2F3algebra

If n=0, there is one matrix X, all traces are zero, and primal nonemptiness implies bj≥0 for every j. The primal singleton is compact with optimum 0, while every y≥0 is dual feasible and b⋅y≥0, with equality at y=0. The vector q1=m+1, qj=1 for j≥2 is strictly positive and its empty matrix slack is positive definite in the quadratic-form sense, since there is no nonzero vector. Thus all conclusions hold. Henceforth assume n≥1.

1.2F1F2F3algebra

Regard the Hermitian matrices Hn as a real space with coordinates the n real diagonal entries and the real and imaginary parts above the diagonal, giving Rn2. Direct diagonal summation yields tr⁡(UV)=∑iUiiVii+2∑i<jRe⁡(UijVij‾) for Hermitian U,V. This is a real inner product, with norm ∥U∥F=(∑i,j∣Uij∣2)1/2; all finite linear maps below are continuous in these coordinates. The cone K={X∈Hn:X⪰0} is convex and closed, being the intersection over v∈Cn of the closed real half-spaces v∗Xv≥0.

2.1F2F3F4step 1.2algebra

Direct summation gives tr⁡(Dvv∗)=v∗Dv. For X∈K, write X=∑iλivivi∗ in an orthonormal eigenbasis, with λi≥0. Then tr⁡(X)=∑iλi and ∥X∥F2=tr⁡(X2)=∑iλi2, so ∥X∥F≤tr⁡(X). For D∈K, tr⁡(DX)=∑iλivi∗Dvi≥0. Conversely, a Hermitian D pairing nonnegatively with every X∈K has v∗Dv≥0 by testing X=vv∗, so D∈K. Thus K is self-dual for the real trace pairing. If D is Hermitian with ∥D∥≤1, [F4] gives ∣v∗Dv∣≤∥v∥2, whence −I⪯D⪯I and ∣tr⁡(DX)∣≤tr⁡(X) for X∈K.

3.1givenF1F5F7step 1.2step 2.1algebra

The first constraint gives 0≤tr⁡(X)≤R for every primal feasible X. That feasible set is nonempty, closed by step 1.2 and continuity of its finitely many constraints, and bounded by ∥X∥F≤R. Hence [F5] and [F7] give compactness and attainment of the primal maximum. Step 2.1 with D=C gives ∣tr⁡(CX)∣≤R, so p∗∈[−R,R].

4.1givenF1F2step 2.1step 3.1algebraconstruct

Set q1=m+1 and qj=1 for j≥2. Step 2.1 gives S0:=∑jqjAj−C⪰((m+1)−(m−1)−1)I=I, so q has strictly positive coordinates and positive definite matrix slack. For primal feasible X and dual feasible y, self-duality gives b⋅y−tr⁡(CX)=∑jyj(bj−tr⁡(AjX))+tr⁡((∑jyjAj−C)X)≥0. Thus p∗≤d∗≤b⋅q, and the dual infimum is finite.

5.1F5F6F8step 1.2step 2.1step 4.1algebraconstruct

Put A(X)=(tr⁡(AjX))j and Φ(X,s,a)=(A(X)+s,tr⁡(CX)−a). The image S=Φ(K×R+m×R+) is a nonempty convex cone containing (0,0). To prove it closed, fix z=(u,t)∈S‾ and the open neighborhood V={(u′,t′):∣uj′−uj∣<1 for all j, ∣t′−t∣<1}. For every point of S∩V and every witness (X,s,a), step 4.1 gives tr⁡(X)+∑jsj+a≤tr⁡(S0X)+q⋅s+a=q⋅u′−t′≤∑jqj(∣uj∣+1)+∣t∣+1. With B=∑jqj(∣uj∣+1)+∣t∣+2, all these witnesses belong to the closed bounded set E={(X,s,a):X∈K, tr⁡(X)≤B, 0≤sj≤B, 0≤a≤B} in Rn2+m+1. By [F5] and [F6], Φ(E) is compact and closed, and S∩V⊆Φ(E)⊆S. Every neighborhood U of z has U∩V meeting S, so [F8] gives z∈S∩V‾⊆Φ(E)⊆S. Thus S is closed; no sequence of witness selections was used.

6.1givenF1F9step 3.1step 5.1algebrachoose

Fix γ>p∗. If A(X)+s=b with X∈K,s≥0, then X is primal feasible and tr⁡(CX)−a≤p∗<γ for a≥0. Hence (b,γ)∉S. By [F9] there are w∈Rm and α,β∈R with w⋅u+αt≤β<w⋅b+αγ for every (u,t)∈S. The points (0,−a)∈S for all a≥0 force α≥0. Fix one primal feasible Xf and set sf=b−A(Xf)≥0; then (b,tr⁡(CXf))∈S. If α=0, that point gives the contradiction w⋅b≤β<w⋅b. Thus α>0, using no strictness of Xf or its scalar inequalities.

7.1F1step 2.1step 3.1step 4.1step 5.1step 6.1algebra∎

The coordinate rays (s,0)∈S force wj≤0. Scaling (A(X),tr⁡(CX))∈S by arbitrarily large nonnegative scalars forces tr⁡((∑jwjAj+αC)X)≤0 for every X∈K. Self-duality therefore makes y=−w/α≥0 dual feasible. Since (0,0)∈S, separation gives 0≤β<w⋅b+αγ, so b⋅y<γ. Consequently every γ>p∗ exceeds some dual feasible objective. If d∗>p∗, taking γ=(p∗+d∗)/2 contradicts the definition of d∗. Thus d∗≤p∗, and weak duality gives equality. Step 3.1 supplies primal attainment and the interval. An additionally promised optimal dual witness satisfies b⋅y∗=d∗=p∗ and retains its promised norm bound.

Remarks

The trace bound and norm normalization establish primal compactness and the search interval directly. Strict dual feasibility closes the product-cone image used for separation. Primal nonemptiness alone ensures a nonzero objective coefficient in that separation. The argument proves no unconditional dual attainment; the source's bound r is explicitly a promise about an attained dual optimum.

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